As I’ve mentioned in the past, data is like music, made up of different components, with the spaces, gaps, and rhythm critical to understanding and appreciating the whole. It is an important component of modern businesses, so sellers are exploring new ways to allow businesses to store, interact with, and analyze their data.
In yesteryears, businesses needed to invest in a robust IT infrastructure to ensure their data was properly managed and prepared to be able to correctly analyze it. Even the analysis of this data was frequently the domain of specialized data personnel, with the average, nontechnical business users being unable to perform the complex tasks necessary for analysis.
In 2021, we expect to see the next step of this development, moving from an era of self-service to all-service analytics.
From self-service analytics to all service
Although analytics platforms (also known as business intelligence software) gave businesses the ability to dive deeply into their data, the keys were closely guarded by top-level executives. On this subject, G2’s VP of market research, Tom Pringle notes:
Every decision-maker at every level can benefit from data-driven insights, yet BI software was only in the hands of high-level managers and executives. As a result, vast numbers of potential beneficiaries, including business analysts and sales operations professionals, increased the demand for data analysis software; this led to the rise of self-service BI in the late '90s and early 2000s.
The importance and potential of self service cannot be understated. With a successful self service implementation in place, a sales manager with little to no technical experience, for example, can get a birdseye of view of their team’s performance. The data gives them the ability to properly award high achievers and address any performance issues.
At G2, we have gone through various iterations on how self-service analytics has been represented:
Until 2020, Self Service Business Intelligence was listed on G2 as a separate category from Business Intelligence Platforms (now referred to as Analytics Platforms).
In 2020, the market research team evaluated the taxonomy and determined that self service is not fundamentally a distinct category, but rather a subset of the broader Analytics Platforms category. As such, self service is currently listed as an attribute of analytics platforms, as can be seen below.
Even in the era of self service, analytics can too easily get siloed and become the tool of the few. Data enthusiasts and users within the business are given access to easy-to-use dashboards galore and are able to digest a wide range of useful data insights. However, too often this data is not shared and remains in the hands and purview of only a handful of individuals. This sad reality is based on the fact that individuals are focusing on their own needs and desires and the current analytics toolbox is not overly conducive to data sharing and collaboration. Indeed, there is a reason why it is called self service.
The next frontier is what we are calling‘all service’, which has variably been called ‘active intelligence’, ‘business cloud’, and more. More than a new set of technologies, this is a new way of thinking, in which the analysis of data is easily accomplished, shared, and reproduced. This form of analysis is fundamentally a subset of self service, inasmuch as it can be accomplished without data professionals.
Emerging features which are facilitating this revolution include:
Active, intelligent alerting, powered by machine learning (triggered by anomalies in data)
Notebooks and workspaces which facilitate real-time collaboration
With these innovations in place, businesses will be able to more easily understand their data and work together to make data-driven decisions. They will be able to communicate around, with, and to their data. By embracing the age of all service, businesses will gain a competitive advantage and achieve success.
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Matthew Miller is passionate about emerging technology and its impact on society and businesses. He most recently worked as an AI Research Analyst at CognitionX, a London-based AI-powered Knowledge Network and host of one of Europe's largest Ai conferences. He also co-founded a pro bono voice technology group, VAICE, which has helped companies discover the best ways to incorporate voice tech in their business and their business models. At G2, he is focusing on the AI and Analytics categories and looks forward to learning more. Get in touch at email@example.com.